Actas de congresos
Stochastic Processes And Copula Model Applied In The Economic Evaluation For Brazilian Oil Fields Projects
Spe Hydrocarbon Economics And Evaluation Symposium. Society Of Petroleum Engineers (spe), v. , n. , p. 379 - 399, 2014.
Over the last two decades, the stochastic processes and copula theories have been widely used in financial analysis, especially in the conditional variance models. Nevertheless, there are few applications cases addressing to the economic evaluation of E&P projects. In such context, the present paper proposes a comprehensive methodology for integration of these theories to the economic evaluation based on discounted cash flow under uncertainty of E&P projects. A cash flow simulator was specially built for the purpose, enabling the applications these theories on the relevant econometric variables. Some simulations are performed with production curves modeled by a set of analytic functions, including: linear function for the start of production until the plateau, exponential function for production decline curve and sigmoid functions for water curves (injection and production). All models were validated against curves derived from reservoir flow simulators. Four models are shown in this paper: two models for forecasting oil price based on GARCH(1,1) and EGARCH(1,1), one model for the attractiveness minimum rate based on ARMA(1,1) and the last one refers to a model based on Gumbel copula for the CAPEX and OPEX values. The models are applied to predict NPV by cash flow simulator and were performed using the current fiscal regimes valid in Brazil, considering the tax system and production sharing contracts. In the both cases, this paper including the legal details related to the government take. The aim of these models is to determine the breakeven oil price for projects on the Brazilian pre-salt fields. The main contribution of the present work is to provide analysts with a tool and a methodology to anticipate risk analysis of Brazilian oil fields projects based on VaR and A VaR measures. 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